Representation and Accountability II

Carolina Torreblanca

University of Pennsylvania

Global Development: Intermediate Topics in Politics, Policy, and Data

PSCI 3200 - Spring 2025

Agenda

Dunning et al. (2019)

Democracy and Accountability


Basic idea thus far:

  • If voters can observe how politicians behave, votes can discipline politicians

    • Politicians want to be reelected
    • Voters reelect good performing politicians
    • Politicians exert effort to be better

Democracy and Accountability

 

Funders have had the same idea!

  • A lot of money has been spent on “information interventions”
    • Tell voters of politicians’ good/bad behavior
  • And yet, we do not really know if they work
    • It has been difficult to accumulate information

Barriers hindering accumulation


What is accumulation?

  • Building knowledge across studies

What makes it difficult?

  • Limited replication
  • Heterogeneity of design and measurement
  • Publication bias

Publication bias

  • Do you think it is easier to publish a study that finds an effect or one that does not find any effect?

  • What are the consequences for what we, as a discipline, think we know?

Facilitating accumulation


What solutions are discussed by the authors?

  • Pre-registration
  • Harmonizing theory, measurement, and estimation
  • Publication of null results

Facilitating accumulation

Models of political accountability

Accountability requires that voters:

  • Observe performance
    • Attribution (who’s fault?)
    • Benchmarking (is this good or bad relative to what I thought?)
  • Update their beliefs (learn from what they see)
  • Have credible alternatives

Models of political accountability

What does the literature say?

  • Theory is mixed
    • Partisan and sectarian attachments are strong
    • Voters may be reluctant to update their beliefs
  • Experimental results are mixed
    • Demobilization
    • Limited recall
    • Ephemeral effects

Research Design

Intervention

  • Information on political performance
    • Legislative behavior
    • Spending irregularities
    • Budget allocation
    • Candidate experience

Research Design

Accountability requires that voters:

  • Observe credible signal of performance
    • Attribution
    • Benchmarking
  • Update their beliefs
    • Good news: \(Q > P \mid 1(P = Q, Q > med(Q) )\)
  • Have credible alternatives

Ecological Validity


  • How is information disseminated?
  • What is the real world activity being tested?

Describing Information

Research Design


Core hypotheses:

  1. Good news increases voter support for incumbents
  2. Bad news decreases voter support for incumbents
  3. Effect of information will increase with gap between Q and P
  4. Strongest for nonpartisan and non-coethnic voters

Findings

Findings

Why the null results?

  • Source credibility?
    • No…
  • Lack of retention?
  • Lack of updating on politician performance?
  • Lack of updating about politician quality?
  • Intervention is too weak?

Statistical Power


Can we update on “null results”?

  • Statistical power is the probability of correctly detecting a true effect in a study

  • Higher power reduces the risk of a false negative

    • The larger your sample size and the bigger the effect size, the more powered you are, for a given level of statistical significance

Statistical Power

Recall the interpretation of p-values:

  • The probability of observing a test statistic at least as extreme as the one you observed if the true parameter value is zero
  • Or, the probability of rejecting the null hypothesis when the null was true
  • This is called a “Type I” error: a false positive
  • We also have “Type II” errors: a false negative

Statistical Power

Power is the probability of correctly accepting the alternative hypothesis

  • The probability of a true positive

    • Equals (1 - probability of type II error)

    • The common threashold in the discipline is 80% power

You can check out the EGEN power calculator to understand better

Statistical Power

Null results were not “foregone conclusion”?

  • 80% power
  • Change the vote of 5/100 voters
  • Change turnout of 4/100 voters

Findings

Findings

Findings

Policy Implications

  • Much of the work funded by donors is probably not having an impact on accountability
  • Targeting of information provision needs to be rethought
    • Public dissemination and coordination